org.encog.neural.pattern
Class SVMPattern

java.lang.Object
  org.encog.neural.pattern.SVMPattern

All Implemented Interfaces:

NeuralNetworkPattern

public class SVMPattern
extends Object
implements NeuralNetworkPattern

A pattern to create support vector machines.

Constructor Summary

SVMPattern()

Method Summary

void	addHiddenLayer(int count) Unused, a BAM has no hidden layers.
void	clear() Clear any settings on the pattern.
MLMethod	generate() Generate the specified neural network.
int	getInputNeurons()
int	getOutputNeurons()
boolean	isRegression()
void	setActivationFunction(ActivationFunction activation) Not used, the BAM uses a bipoloar activation function.
void	setInputNeurons(int count) Set the number of input neurons.
void	setKernelType(KernelType kernelType) Set the kernel type.
void	setOutputNeurons(int count) Set the number of output neurons.
void	setRegression(boolean regression) Set if regression is used.
void	setSVMType(SVMType svmType) Set the SVM type.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SVMPattern

public SVMPattern()

Method Detail

addHiddenLayer

public final void addHiddenLayer(int count)

Unused, a BAM has no hidden layers.

Specified by:

addHiddenLayer in interface NeuralNetworkPattern

Parameters:

count - Not used.

clear

public final void clear()

Clear any settings on the pattern.

Specified by:

clear in interface NeuralNetworkPattern

generate

public final MLMethod generate()

Description copied from interface: NeuralNetworkPattern

Generate the specified neural network.

Specified by:

generate in interface NeuralNetworkPattern

Returns:

The generated network.

getInputNeurons

public final int getInputNeurons()

Returns:

The input neuron count.

getOutputNeurons

public final int getOutputNeurons()

Returns:

The input output count.

isRegression

public final boolean isRegression()

Returns:

True, if this is regression.

setActivationFunction

public final void setActivationFunction(ActivationFunction activation)

Not used, the BAM uses a bipoloar activation function.

Specified by:

setActivationFunction in interface NeuralNetworkPattern

Parameters:

activation - Not used.

setInputNeurons

public final void setInputNeurons(int count)

Set the number of input neurons.

Specified by:

setInputNeurons in interface NeuralNetworkPattern

Parameters:

count - The number of input neurons.

setKernelType

public final void setKernelType(KernelType kernelType)

Set the kernel type.

Parameters:

kernelType - The kernel type.

setOutputNeurons

public final void setOutputNeurons(int count)

Set the number of output neurons.

Specified by:

setOutputNeurons in interface NeuralNetworkPattern

Parameters:

count - The output neuron count.

setRegression

public final void setRegression(boolean regression)

Set if regression is used.

Parameters:

regression - True if regression is used.

setSVMType

public final void setSVMType(SVMType svmType)

Set the SVM type.

Parameters:

svmType - The SVM type.